Towards Increased Productivity of Algorithm Implementation

Robert Paige

ONR Grant N00014-93-I-0924


                                    | Scientific Question: 
                                    | How can programming language concepts
                                    | lead to algorithmic results?


Scientific Approach:                | Proven Results Published in 1995:
                                    |
1. Type/subtype system abstracts    |1.Theta(mn + n**2) time Ready Simulation
sequential RAM model of computation,|algorithm; improves Omega(mn**6) solution
and makes a high level set theoretic|2.  Two new space/time improved algorithms
language computationally transparent|for DFA minimization
                                    |3. Over a dozen algorithms that solve
2.  Language abstraction captures   |Programming Language Problems improved 
complexity and replaces counting    |from Omega(f) hash operations to O(f) in 
arguments by a more syntactic and   |the worst case
algebraic worst case and amortized  |
algorithmic analysis                |(New and Unpublished)
                                    |
                                    |4.  Linear expected time fragment of
                                    |Willard's RCS Database Query Language
                                    |improved to linear worst case time


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